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A Stochastic EM Algorithm with Sampling-Importance Resampling for Missing Data in Regression with Nonlinear Predictors
Estimating regression models with nonlinear predictor transformations is challenging when data are missing, because nonlinearity typically renders the conditional distribution of the missing values intractable. Previous methods require specific nonlinear forms, such as polynomials or interactions, o
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